In Long-Term Evolution (LTE), single-carrier frequency-division multiple-access (SC-FDMA) is used in the uplink. SC-FDMA is advantageous in terms of power amplifier efficiency as it has a smaller peak-to-average power ratio (PAPR) than an orthogonal frequency division multiple access (OFDMA) signal. SC-FDMA, however, gives rise to an inter-symbol interference (ISI) problem in dispersive channels. It is important to address ISI so that SC-FDMA can improve power amplifier efficiency without sacrificing performance.
When LTE is first rolled out, it is likely that linear minimum mean square error (LMMSE) receivers will be implemented in the base station, also referred to as an eNodeB. LMMSE receivers suppress ISI using linear frequency-domain equalization, where the filter coefficients are designed to maximize the signal-to-interference-plus-noise ratio (SINR) for each subcarrier component. Compared to a simple match filtering receiver, LMMSE provides a significant performance improvement.
But it is thought that even better performance can be achieved by employing even more advanced receiver techniques. For example, there have been interests in using a turbo receiver (or turbo equalizer) in uplink LTE to improve performance in ISI channels beyond LMMSE. However, the complexity of a turbo receiver is high. Thus, it is advantageous to turn on the iterative turbo processing only when there is a good chance of performance improvement from the turbo processing.
A method has been proposed to adaptively switch on and off the iterative turbo operation. This previous method is based on the post-equalization SINR's of an MMSE receiver and a turbo receiver. Comparing these two SINR gives rise to a gain factor G. In the calculation of the turbo receiver SINR, it is assumed that the ISI in the turbo receiver is completely removed. The previous method further depends on an estimated average bit error rate (BER) indicator, B. Whether the iterative turbo operation is activated or not is determined based on G and B.
While the previous method has been shown to be effective, an even better solution may be achievable through estimating performance using, for example, a capacity-achieving receiver.